Differential binding studies applying functional protein microarrays and surface plasmon resonance

A variety of different in vivo and in vitro technologies provide comprehensive insights in protein-protein interaction networks. Here we demonstrate a novel approach to analyze, verify and quantify putative interactions between two members of the S100 protein family and 80 recombinant proteins derived from a proteome-wide protein expression library. Surface plasmon resonance (SPR) using Biacore technology and functional protein microarrays were used as two independent methods to study protein-protein interactions. With this combined approach we were able to detect nine calcium-dependent interactions between Arg-Gly-Ser-(RGS)-His6 tagged proteins derived from the library and GST-tagged S100B and S100A6, respectively. For the protein microarray affinity-purified proteins from the expression library were spotted onto modified glass slides and probed with the S100 proteins. SPR experiments were performed in the same setup and in a vice-versa approach reversing analytes and ligands to determine distinct association and dissociation patterns of each positive interaction. Besides already known interaction partners, several novel binders were found independently with both detection methods, albeit analogous immobilization strategies had to be applied in both assays

Using Drones to Determine Chimpanzee Absences at the Edge of Their Distribution in Western Tanzania

Effective species conservation management relies on detailed species distribution data. For many species, such as chimpanzees (Pan troglodytes), distribution data are collected during ground surveys. For chimpanzees, such ground surveys usually focus on detection of the nests they build instead of detection of the chimpanzees themselves due to their low density. However, due to the large areas they still occur in, such surveys are very costly to conduct and repeat frequently to monitor populations over time. Species distribution models are more accurate if they include presence as well as absence data. Earlier studies used drones to determine chimpanzee presence using nests. In this study, therefore, we explored the use of drones to determine the absence of chimpanzee nests in areas we flew over on the edge of the chimpanzee distribution in western Tanzania. We conducted 13 flights with a fixed-wing drone and collected 3560 images for which manual inspection took 180 h. Flights were divided into a total of 746 25 m2 plots for which we determined the absence probability of nests. In three flights, we detected nests, in eight, absence was assumed based on a 95% probability criterion, and in two flights, nest absence could not be assumed. Our study indicates that drones can be used to cover relatively large areas to determine the absence of chimpanzees. To fully benefit from the usage of drones to determine the presence and absence of chimpanzees, it is crucial that methods are developed to automate nest detection in images

The 20S Proteasome Splicing Activity Discovered by SpliceMet

The identification of proteasome-generated spliced peptides (PSP) revealed a new unpredicted activity of the major cellular protease. However, so far characterization of PSP was entirely dependent on the availability of patient-derived cytotoxic CD8+ T lymphocytes (CTL) thus preventing a systematic investigation of proteasome-catalyzed peptide splicing (PCPS). For an unrestricted PSP identification we here developed SpliceMet, combining the computer-based algorithm ProteaJ with in vitro proteasomal degradation assays and mass spectrometry. By applying SpliceMet for the analysis of proteasomal processing products of four different substrate polypeptides, derived from human tumor as well as viral antigens, we identified fifteen new spliced peptides generated by PCPS either by cis or from two separate substrate molecules, i.e., by trans splicing. Our data suggest that 20S proteasomes represent a molecular machine that, due to its catalytic and structural properties, facilitates the generation of spliced peptides, thereby providing a pool of qualitatively new peptides from which functionally relevant products may be selected

J. Biol. Chem.

The potential of a protein-engineered His tag to immobilize macromolecules in a predictable orientation at metal-chelating lipid interfaces was investigated using recombinant 20 S proteasomes His-tagged in various positions. Electron micrographs demonstrated that the orientation of proteasomes bound to chelating lipid films could be controlled via the location of their His tags: proteasomes His-tagged at their sides displayed exclusively side-on views, while proteasomes His-tagged at their ends displayed exclusively end-on views. The activity of proteasomes immobilized at chelating lipid interfaces was well preserved. In solution, His-tagged proteasomes hydrolyzed casein at rates comparable with wild- type proteasomes, unless the His tags were located in the vicinity of the N termini of alpha-subunits. The N termini of a-subunits might partly occlude the entrance channel in a-rings through which substrates enter the proteasome for subsequent degradation. A combination of electron micrographs and atomic force microscope topographs revealed a propensity of vertically oriented proteasomes to crystallize in two dimensions on fluid lipid films. The oriented immobilization of His-tagged proteins at biocompatible lipid interfaces will assist structural studies as well as the investigation of biomolecular interaction via a wide variety of surface-sensitive techniques including single-molecule analysis

Fusion moves for graph matching

We contribute to approximate algorithms for the quadratic assignment problem also known as graph matching. Inspired by the success of the fusion moves technique developed for multilabel discrete Markov random fields, we investigate its applicability to graph matching. In particular, we show how fusion moves can be efficiently combined with the dedicated state-of-the-art dual methods that have recently shown superior results in computer vision and bioimaging applications. As our empirical evaluation on a wide variety of graph matching datasets suggests, fusion moves significantly improve performance of these methods in terms of speed and quality of the obtained solutions. Our method sets a new state-of-the-art with a notable margin with respect to its competitors

Specific orientation and two-dimensional crystallization of the proteasome at metal-chelating lipid interfaces

The potential of a protein-engineered His tag to immobilize macromolecules in a predictable orientation at metal-chelating lipid interfaces was investigated using recombinant 20 S proteasomes His-tagged in various positions. Electron micrographs demonstrated that the orientation of proteasomes bound to chelating lipid films could be controlled via the location of their His tags: proteasomes His-tagged at their sides displayed exclusively side-on views, while proteasomes His-tagged at their ends displayed exclusively end-on views. The activity of proteasomes immobilized at chelating lipid interfaces was well preserved. In solution, His-tagged proteasomes hydrolyzed casein at rates comparable with wild- type proteasomes, unless the His tags were located in the vicinity of the N termini of alpha-subunits. The N termini of a-subunits might partly occlude the entrance channel in a-rings through which substrates enter the proteasome for subsequent degradation. A combination of electron micrographs and atomic force microscope topographs revealed a propensity of vertically oriented proteasomes to crystallize in two dimensions on fluid lipid films. The oriented immobilization of His-tagged proteins at biocompatible lipid interfaces will assist structural studies as well as the investigation of biomolecular interaction via a wide variety of surface-sensitive techniques including single-molecule analysis

A comparative study of graph matching algorithms in computer vision

The graph matching optimization problem is an essential component for many tasks in computer vision, such as bringing two deformable objects in correspondence. Naturally, a wide range of applicable algorithms have been proposed in the last decades. Since a common standard benchmark has not been developed, their performance claims are often hard to verify as evaluation on differing problem instances and criteria make the results incomparable. To address these shortcomings, we present a comparative study of graph matching algorithms. We create a uniform benchmark where we collect and categorize a large set of existing and publicly available computer vision graph matching problems in a common format. At the same time we collect and categorize the most popular open-source implementations of graph matching algorithms. Their performance is evaluated in a way that is in line with the best practices for comparing optimization algorithms. The study is designed to be reproducible and extensible to serve as a valuable resource in the future. Our study provides three notable insights: 1.) popular problem instances are exactly solvable in substantially less than 1 second and, therefore, are insufficient for future empirical evaluations; 2.) the most popular baseline methods are highly inferior to the best available methods; 3.) despite the NP-hardness of the problem, instances coming from vision applications are often solvable in a few seconds even for graphs with more than 500 vertices